IS ARTIFICIAL INTELLIGENCE THE BOTTLENECK TO OMNICHANNEL ENGAGEMENT?
You have strategized and planned and have the perfect portfolio of promotions to engage your customers. The customer journey will be unrivaled in your market and all that is left to do is to give the word to start. But wait…who will get what and when? Given that omnichannel is predicated on coordinated and personalized interactions, you can’t just let the individual channel owners execute the promotions based on legacy target lists; that would be rote multi-channel execution and you are moving beyond that. Somehow you have to get a list, by customer, of what promotion to execute, and when, and get that to the various execution teams. Oh, and you will have to generate that list weekly to capture changing customer preferences and to continually adjust your mix.
The description above is not meant to make light of a complex topic but to make a point. Analyzing customer preferences, and determining the optimal next interaction with each, is at the core of omnichannel engagement. Given the complexity of these analytics, they will need to be generated by artificial intelligence/machine learning (AI/ML). You either believe that or you don’t, but let’s assume you do.
AI/ML is not for the faint of heart. It takes a lot of data (real or synthesized), highly experienced and creative data scientists developing the models, and a new breed of operations experts to put the analytics into production. At Sentier, we have been doing this for 6 years and our approach is still evolving. So, to finally answer the question, AI/ML is definitively a bottleneck to true omnichannel engagement in pharma. Where are the roadblocks coming from?
Data - In short, AI/ML wants to see it all, but in a structured way. The answer is not the data lake or the data warehouse. It is a new structure that has to be built. We call it the analytic data layer or the “AI Depot”.
Data Scientists (?) - This is about staffing and the question mark is here because companies have done a lot of hiring of data scientists over the last couple of years. But do they really have the required skills and knowledge of commercial pharma to deliver the analytics?
Development - Some very innovative and game changing analytics are being developed but in silos. These analytics never see broad adoption across the organization and they are not being leveraged for omnichannel. Required omnichannel analytics have to be developed in a consistent way that lends itself to eventual sharing and deployment.
Operations - As our head of product development would say, there is no playbook for AI/ML operations that you can go get. This is an evolving space and everyone is trying to figure it out. How can you have it if “it” doesn’t exist?
Politics - You are never supposed to talk politics in business but we are talking about company politics. Marketing and Sales executives have a lot of say in what goes on and how it gets done. These leaders need to buy into the benefit of having AI/ML direct their activities which is no small task. Getting to a true, fluid state of omnichannel requires bold leadership and the willingness to continually innovate.
The good news is that everyone involved, pharma companies, vendors, academia, will figure out how to get past all of these roadblocks to successfully implement AI/ML to support omnichannel engagement. People will say “of course they will because other industries do it”. To those people, I would say there is some borrowing to be done but pharma has some very specific nuances to be accounted for and it will take some time.
We are holding a webinar on November 15th to start the conversation on AI operations to support omnichannel. We hope you can join us to lend your thoughts and to start getting ideas on how you will overcome the AI/ML bottleneck to get your omnichannel efforts moving.
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SENTIER was founded in 2017 to disrupt analytic insight generation and delivery in Pharma. Through VELOCITY, the industry leading Analytic Operations as a Service (AOaaS) platform, our customers are able to maximize the ROI on AI and ML activities by allowing non-data scientists to deliver answers as frequently as the business demands. We also support our clients with advanced marketing & sales analytics and support services designed to prepare models and data pipelines for production. SENTIER believes that the ethical application of solutions will benefit patients and health care providers as well as the Pharma and Biotech companies we work with.
